Fingerprints have been used by law enforcement and forensics experts to successfully identify people for more than 100 years. Though fingerprints are assumed to be infallible personal identifiers, there has been little scientific research to prove this claim to be true. As such, there have been repeated challenges to the admissibility of fingerprint evidence in courts of law.
"We wanted to answer the question that has plagued law enforcement and forensic science for decades: Is fingerprint pattern persistent over time?" said Anil Jain, University Distinguished Professor, computer science and engineering, at Michigan State University. "We have now determined, with multilevel statistical modeling, that fingerprint recognition accuracy remains stable over time."
Jain, along with his former Ph.D. student Soweon Yoon, who is now with the National Institute of Standards and Technology, used fingerprint records of 15,597 subjects apprehended multiple times by the Michigan State Police over a time span varying from five to 12 years.
The results show that fingerprint recognition accuracy doesn't change even as the time between two fingerprints being compared increases.
The paper by Yoon and Jain, published in the Proceedings of the National Academy of Sciences , is the largest and most thorough study of the persistence of Automated Fingerprint Identification Systems, or AFIS, accuracy.
Experts agree that Jain's research addresses one of the most fundamental issues in fingerprint identification and is of great importance to law enforcement and forensic science:
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Jain's research was supported by a grant from the National Science Foundation Center for Identification Technology Research.
NIST is a nonregulatory agency of the Commerce Department that promotes U.S. innovation and industrial competitiveness by advancing measurement science, standards and technology in ways that enhance economic security and improve our quality of life. For more information, visit http://www.nist.gov .
Proceedings of the National Academy of Sciences